Minor weaknesses dot these teams. Except for Arizona, which needs to bring in more help to really run Bruce Arians' offense.
11 Oct 2012
by Brian Fremeau
The No. 1 team in the country according to FEI is scoring 52 points per game (fifth most nationally) and 4.2 points per possession (second most nationally). Its offense leads the nation in explosive drive percentage (31.1 percent) and points per ordinary drive (2.7), ranks second in value drive percentage (67.4 percent), and third in available yards percentage (66.4 percent). There’s no dispute that West Virginia has one of the most dangerous offenses in college football.
The Mountaineers have also given up 108 points in the last two games and rank 112th overall in raw defensive efficiency and 111th overall in special teams efficiency. Can West Virginia truly be the nation’s best team if it only plays exceptionally well in only one of three phases of the game? It certainly doesn’t seem likely to be sustainable.
The primary reason West Virginia ranks first overall is tied up in a bit of circular logic. There are five teams from the Big 12 ranked among the top 10 in this week’s FEI ratings (including West Virginia’s last two opponents, No. 6 Texas and No. 9 Baylor) and four others rank among the top 30. Aside from Kansas, conference collectively beat down on its non-conference opponents in such efficient fashion that they are all receiving a collective boost by having played a couple of games apiece against one another. With even more to come –- the conference plays a round-robin schedule -– FEI may continue to reward the league, though I expect there will eventually be some separation.
What’s interesting to me is that while FEI thinks very highly of the league, it doesn’t think very highly of the league’s chance to send a team to the BCS championship game. Only West Virginia and Oklahoma are projected to win more than five more games the rest of the way, meaning FEI thinks that only the Mountaineers will get to double-digit victories by season’s end. FEI says that teams in other conferences have a better chance to get to 10 or more wins: Alabama, Oregon, Florida, Florida State, and Notre Dame.
A very intriguing strength of schedule debate may present itself over the course of the coming months. It seems blasphemous to suggest that an SEC team may not have a schedule strength argument, but Alabama has the 78th-toughest regular season schedule according to current FEI ratings, weaker than traditional AQ conference schedules and much weaker than traditional SEC schedules. Alabama’s dominance of its schedule, however weak, will make this a non-issue, but in a scenario in which 1-loss teams will need to be parsed, the SEC may actually hold the Crimson Tide back.
This is the final week in which preseason data is still used as a component in the FEI ratings. Starting next week, preseason data will be eliminated, and we will debut the complete offensive, defensive, and special teams opponent-adjusted ratings for all teams. Let the arguments begin.
This weekly feature identifies the games played each week that were most impacted by turnovers, special teams, field position, or some combination of the three. The neutralized margin of victory is a function of the point values earned and surrendered based on field position and expected scoring rates.
| Week 6 Games In Which Total Turnover Value Exceeded Non-Garbage Final Score Margin | |||||||||||||||||
| Date | Winning Team | Non-Garbage Final Score |
Losing Team | TTV + |
TTV - |
TTV Net |
TO Neutral Score Margin |
||||||||||
| 10/5 | BYU | 6-3 | Utah State | 6.8 | 3.0 | 3.8 | -0.8 | ||||||||||
| 10/5 | Syracue | 14-13 | Pittsburgh | 7.8 | 4.8 | 3.0 | -2.0 | ||||||||||
| 10/6 | Idaho | 26-18 | New Mexico State | 14.3 | 5.8 | 8.5 | -0.5 | ||||||||||
| 10/6 | Iowa State | 37-23 | TCU | 23.4 | 2.1 | 21.3 | -7.3 | ||||||||||
| 10/6 | Navy | 28-21 | Air Force | 11.9 | 0.0 | 11.9 | -4.9 | ||||||||||
| 10/6 | Ohio | 38-31 | Buffalo | 11.8 | 2.0 | 9.8 | -2.8 | ||||||||||
| 10/6 | Temple | 37-28 | South Florida | 11.0 | 0.0 | 11.0 | -2.0 | ||||||||||
| 10/6 | Tulsa | 45-38 | Marshall | 12.6 | 3.7 | 8.9 | -1.9 | ||||||||||
| Week 6 Games In Which Special Teams Value Exceeded Non-Garbage Final Score Margin | |||||||||||||||||
| Date | Winning Team | Non-Garbage Final Score |
Losing Team | STV + |
STV Neutral Score Margin |
||||||||||||
| 10/6 | Idaho | 26-18 | New Mexico State | 9.0 | -1.0 | ||||||||||||
| 10/6 | Memphis | 14-10 | Rice | 5.3 | -1.3 | ||||||||||||
| 10/6 | Ohio | 38-31 | Buffalo | 15.1 | -8.1 | ||||||||||||
| Week 6 Games In Which Field Position Value Exceeded Non-Garbage Final Score Margin | |||||||||||||||||
| Date | Winning Team | Non-Garbage Final Score |
Losing Team | FPV + |
FPV - |
FPV Net |
FPV Neutral Score Margin |
||||||||||
| 10/5 | Syracuse | 14-13 | Pittsburgh | 19.4 | 15.7 | 3.7 | -2.7 | ||||||||||
| 10/6 | Army | 34-31 | Boston College | 22.0 | 17.4 | 4.6 | -1.6 | ||||||||||
| 10/6 | Ohio | 38-31 | Buffalo | 38.6 | 16.4 | 22.2 | -15.2 | ||||||||||
| 10/6 | Tulsa | 45-38 | Marshall | 33.9 | 22.7 | 11.2 | -4.2 | ||||||||||
2012 totals to date:
2012 Game Splits for all teams, including the offensive, defensive, special teams, field position, and turnover values recorded in each FBS game are provided here.
The Fremeau Efficiency Index (FEI) rewards playing well against good teams, win or lose, and punishes losing to poor teams more harshly than it rewards defeating poor teams. FEI is drive-based and it is specifically engineered to measure the college game.
FEI is the opponent-adjusted value of Game Efficiency (GE), a measurement of the success rate of a team scoring and preventing opponent scoring throughout the non-garbage-time possessions of a game. FEI represents a team's efficiency value over average. Strength of Schedule (SOS) is calculated as the likelihood that an "elite team" (two standard deviations above average) would win every game on the given team's schedule. SOS listed here includes future games scheduled.
Mean Wins (FBS MW) represent the average total games a team with the given FEI rating should expect to win against its complete schedule of FBS opponents. Remaining Mean Wins (FBS RMW) represent the average expected team wins for games scheduled but not yet played.
Offensive Efficiency (OE) is the raw unadjusted efficiency of the given team's offense, a measure of its actual drive success against expected drive success based on field position. Defensive Efficiency (DE) is the raw unadjusted efficiency of the given team's defense, a measure of the actual drive success of its opponents against expected drive success based on field position. Field Position Advantage (FPA) is the share of the value of total starting field position earned by each team against its opponents.
Only games between FBS teams are considered in the FEI calculations. Since limited data is available in the early part of the season, preseason projections are factored into the current ratings. The weight given to projected data will be reduced each week until Week 7, when it will be eliminated entirely. Opponent-adjusted offensive and defensive FEI ratings will also debut in Week 7.
These FEI ratings are a function of results of games played through October 6. The ratings for all FBS teams can be found here.
| Rank | Team | FBS W-L |
FEI | Last Wk |
GE | GE Rk |
SOS | SOS Rk |
FBS MW |
FBS RMW |
OE | OE Rk |
DE | DE Rk |
FPA | FPA Rk |
| 1 | West Virginia | 4-0 | .308 | 10 | .164 | 21 | .032 | 10 | 8.7 | 5.4 | 1.392 | 1 | .495 | 112 | .482 | 76 |
| 2 | Alabama | 5-0 | .304 | 1 | .432 | 1 | .385 | 78 | 10.3 | 5.5 | .335 | 25 | -1.009 | 1 | .612 | 2 |
| 3 | Notre Dame | 5-0 | .280 | 3 | .241 | 6 | .111 | 14 | 10.3 | 5.8 | .245 | 34 | -.756 | 5 | .515 | 48 |
| 4 | Kansas State | 4-0 | .278 | 7 | .333 | 3 | .016 | 5 | 7.9 | 4.7 | .802 | 4 | -.160 | 44 | .593 | 3 |
| 5 | Oklahoma | 2-1 | .260 | 9 | .176 | 17 | .017 | 6 | 8.5 | 6.1 | .349 | 24 | -.430 | 20 | .506 | 55 |
| 6 | Texas | 4-1 | .258 | 2 | .229 | 7 | .022 | 7 | 8.6 | 4.6 | .887 | 3 | .329 | 96 | .591 | 5 |
| 7 | Florida | 5-0 | .235 | 5 | .182 | 16 | .189 | 28 | 9.0 | 4.8 | .031 | 62 | -.524 | 14 | .543 | 23 |
| 8 | Florida State | 3-1 | .235 | 4 | .200 | 13 | .367 | 72 | 8.5 | 5.1 | .260 | 32 | -.418 | 22 | .576 | 7 |
| 9 | Baylor | 2-1 | .219 | 25 | .163 | 22 | .009 | 2 | 6.4 | 4.6 | 1.269 | 2 | 1.065 | 123 | .575 | 8 |
| 10 | South Carolina | 6-0 | .213 | 12 | .320 | 4 | .304 | 56 | 9.2 | 3.5 | .192 | 41 | -.942 | 3 | .542 | 24 |
| 11 | Oregon | 5-0 | .204 | 8 | .367 | 2 | .259 | 43 | 8.9 | 4.2 | .514 | 12 | -.624 | 6 | .535 | 34 |
| 12 | Texas Tech | 3-1 | .198 | 6 | .197 | 14 | .022 | 8 | 6.5 | 3.7 | .636 | 7 | -.175 | 41 | .499 | 62 |
| Rank | Team | FBS W-L |
FEI | Last Wk |
GE | GE Rk |
SOS | SOS Rk |
FBS MW |
FBS RMW |
OE | OE Rk |
DE | DE Rk |
FPA | FPA Rk |
| 13 | Ohio State | 6-0 | .190 | 24 | .174 | 19 | .360 | 69 | 9.9 | 4.8 | .397 | 19 | -.242 | 36 | .513 | 49 |
| 14 | Cincinnati | 3-0 | .171 | 11 | .264 | 5 | .448 | 84 | 7.9 | 5.2 | .386 | 20 | -.580 | 9 | .568 | 9 |
| 15 | Texas A&M | 3-1 | .166 | 38 | .219 | 9 | .164 | 23 | 7.0 | 4.1 | .561 | 10 | -.349 | 27 | .542 | 26 |
| 16 | Iowa State | 3-1 | .160 | 58 | .054 | 54 | .023 | 9 | 5.4 | 2.9 | -.311 | 94 | -.467 | 19 | .529 | 38 |
| 17 | USC | 4-1 | .154 | 18 | .206 | 11 | .213 | 31 | 8.5 | 4.5 | .148 | 48 | -.476 | 17 | .540 | 27 |
| 18 | Arizona State | 3-1 | .152 | 26 | .168 | 20 | .268 | 47 | 8.0 | 4.7 | .183 | 42 | -.535 | 13 | .554 | 19 |
| 19 | Rutgers | 4-0 | .149 | 16 | .136 | 29 | .409 | 81 | 8.5 | 5.3 | .043 | 59 | -.519 | 16 | .548 | 21 |
| 20 | Michigan State | 4-2 | .145 | 17 | .085 | 45 | .244 | 40 | 8.5 | 4.5 | -.108 | 73 | -.520 | 15 | .492 | 71 |
| 21 | Oregon State | 4-0 | .138 | 32 | .072 | 48 | .272 | 50 | 7.4 | 4.5 | -.068 | 68 | -.400 | 26 | .498 | 64 |
| 22 | Oklahoma State | 1-2 | .136 | 27 | .070 | 49 | .014 | 3 | 5.0 | 3.1 | .747 | 5 | .379 | 102 | .444 | 111 |
| 23 | Louisiana Monroe | 3-2 | .122 | 41 | .133 | 30 | .516 | 92 | 10.0 | 6.6 | .677 | 6 | -.009 | 60 | .499 | 61 |
| 24 | Michigan | 3-2 | .121 | 23 | .089 | 42 | .082 | 12 | 7.6 | 4.8 | .201 | 40 | -.255 | 33 | .480 | 80 |
| 25 | BYU | 3-2 | .118 | 59 | .144 | 26 | .259 | 42 | 8.0 | 3.9 | -.227 | 89 | -.992 | 2 | .500 | 59 |
8 comments, Last at 12 Oct 2012, 5:50pm by cfn_ms
Comments
Re: FEI Week 6: Big 12 Taking Charge
It's funny how FEI and S+P do this - and then what ends up happening conference by conference. Because all the OOC games are early in the season (mostly) the strength of schedule basically gets set early on - and in this case, very differently depending on the conference.
We talked before about integrating FCS games into the data to get a bit more connectivity; have you made any progress towards this?
Re: FEI Week 6: Big 12 Taking Charge
This same scenario unfolded a few years ago (I think 2009) with the FEI and the ACC, which was an average conference that "beat each other up."
Will
Re: FEI Week 6: Big 12 Taking Charge
FCS games don't really add connectivity unless you treat them as the "same" opponent. Even if I did consider every FCS opponent as equivalent to the No. 125 team, it would barely register with the top teams since the relevance factor of those games would be so low.
Re: FEI Week 6: Big 12 Taking Charge
Yeah, sorry, they were two separate points. One was asking about how FEI rebalances between divisions once biases are set (or if it does at all); the other was asking about using FCS as more data.
And while FCS doesn't improve connectivity it can improve (or reduce) overall value of wins and losses.
factoring in AA games can
reduce the noise that comes from the rest of the games (more data points = less variance), but it introduces a fairly obvious amount of bias/variance. This is because how you interpret the AA data is drastically dependent on:
how you value blowouts;
how you calculate/factor in schedule (how you weight W/L vs margin/game stats vs schedule strength is something that can lead to massive variation from one system to another when it comes to rating big blowouts over atrocious opponents)
how you compare the AA opponents to each other or 1-A in general (if "AA" is all one bucket, then you get a bias favoring those who play the worst of the lot and hurting those who play relatively less awful AA's);
and probably other things that escape me.
Ultimately, I can see the argument for factoring it in, but I've elected not to for a while and I remain totally comfortable with that, even though it does sometimes lead to missed data (the very rare AA upset over a top 40 team, or just the somewhat rare AA near-upset over a top 40 team)
Re: FEI Week 6: Big 12 Taking Charge
Also - how is garbage time determined per game?
Re: FEI Week 6: Big 12 Taking Charge
I calculate garbage time as a function of the score and the remaining possessions in the game. It's a retroactive designation.
Re: FEI Week 6: Big 12 Taking Charge
So is it a subjective or objective value, then? That's what is confusing; it's tough for me to determine a rule that would (for instance) rule that 50-13 Oregon over Arkansas State was the end of non-garbage time (which was at halftime) vs. 52-14 was the end of non-garbage time vs. Washington (which was well into the 4th quarter and after we had substituted a number of players on both sides).
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